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Record W1997345698 · doi:10.1016/j.jcrs.2003.07.002

Early postoperative refractive outcomes of pediatric intraocular lens implantation

2004· article· en· W1997345698 on OpenAlexaffabout
Eedy Mezer, David S. Rootman, Mohamed Abdolell, Alex V. Levin

Bibliographic record

VenueJournal of Cataract & Refractive Surgery · 2004
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsHospital for Sick ChildrenSickKids FoundationCancer Care OntarioUniversity of Toronto
Fundersnot available
KeywordsMedicineIntraocular lensIntraclass correlationRefractionKeratometerCataract surgeryOphthalmologyRefractive errorIntraocular lens power calculationSurgeryOptometryVisual acuityOpticsPhysics

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate the refractive outcome using 5 intraocular lens (IOL) calculation formulas to determine which best predicts refraction after pediatric cataract surgery. SETTING: The Hospital for Sick Children, Toronto, Ontario, Canada. METHODS: This study comprised a review of the charts of 158 consecutive patients aged 2 to 17 years old who were operated on by 1 of 2 staff surgeons between May 1992 and April 2000. The surgeons performed a total of 206 cataract extractions with primary or secondary IOL implantation. The measured outcome was the actual refraction 2 to 6 months postoperatively versus the target refraction. Two regression formulas (SRK, SRK II) and 3 theoretical formulas (Holladay 1, Hoffer Q, SRK/T) were used to predict refractive outcome based on preoperative axial length, corneal curvature, IOL power, and the IOL A-constant provided by the manufacturer. RESULTS: Forty-nine patients (59 IOL implantations) with available data 2 to 6 months after surgery were studied. Also analyzed were data from a subset of 31 patients (34 IOL implantations) with available data 2 to 3 months after surgery. There was poor to moderate agreement between the predicted and actual postoperative refractions using the SRK formula (intraclass correlation coefficient [ICC] = 0.50/0.04 [2- to 3-month follow-up/2- to 6-month follow-up]) and good or fair agreement using the other formulas (ICC from 0.60/0.24 for SRK II to 0.67/0.37 for Hoffer Q). The mean difference between the predicted and actual postoperative refractions with all formulas ranged from 1.06 to 1.22 diopters (D)/1.35 to 1.79 D (median 0.81 to 0.99 D/0.94 to 1.40 D; range 3.03 to 5.57 D/6.75 to 9.21 D). Using Holladay 1 and SRK, 9% to 18%/23% to 39% eyes were more than +/-2.00 D off the target outcome refraction. CONCLUSIONS: All 5 IOL power calculation formulas were unsatisfactory in achieving the target refraction. This finding may have implications for predicting long-term outcomes, interpreting previous reports of refractive outcomes, and obtaining preoperative informed consent in a clinical setting.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.350
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations69
Published2004
Admission routes2
Has abstractyes

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